数据分析初步完成。
Cat Tom
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analysis_results/analysis_report.html
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<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8">
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<title>MovieLens Dataset Analysis Report</title>
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<style>
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body { font-family: Arial, sans-serif; margin: 0; padding: 20px; color: #333; }
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.container { max-width: 1200px; margin: 0 auto; }
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h1 { color: #2c3e50; text-align: center; margin-bottom: 30px; }
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h2 { color: #3498db; margin-top: 30px; border-bottom: 1px solid #eee; padding-bottom: 10px; }
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.summary { background-color: #f9f9f9; padding: 15px; border-radius: 5px; margin-bottom: 20px; }
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.gallery { display: flex; flex-wrap: wrap; gap: 20px; justify-content: center; margin-top: 20px; }
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.gallery img { max-width: 100%; height: auto; border-radius: 5px; box-shadow: 0 2px 5px rgba(0,0,0,0.1); }
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.figure { margin-bottom: 30px; text-align: center; }
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.figure img { max-width: 100%; height: auto; border-radius: 5px; box-shadow: 0 2px 5px rgba(0,0,0,0.1); }
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.figure .caption { margin-top: 10px; font-style: italic; color: #666; }
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table { width: 100%; border-collapse: collapse; margin: 20px 0; }
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th, td { padding: 10px; text-align: left; border-bottom: 1px solid #ddd; }
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th { background-color: #f2f2f2; }
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tr:hover { background-color: #f5f5f5; }
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</style>
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</head>
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<body>
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<div class="container">
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<h1>MovieLens Dataset User-Movie Preference Analysis Report</h1>
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<div class="summary">
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<h2>Data Overview</h2>
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<p>This analysis is based on the MovieLens dataset, containing 6040 users、3883 movies and 1000209 original rating records。</p>
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</div>
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<h2>User Profile Analysis</h2>
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<div class="figure">
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<img src="user_analysis/gender_distribution.png" alt="用户性别分布">
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<p class="caption">User Gender Distribution</p>
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</div>
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<div class="figure">
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<img src="user_analysis/age_distribution.png" alt="用户年龄分布">
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<p class="caption">User Age Distribution</p>
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</div>
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<div class="figure">
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<img src="user_analysis/occupation_distribution.png" alt="用户职业分布">
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<p class="caption">User Occupation Distribution</p>
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</div>
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<h2>Movie Distribution Analysis</h2>
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<div class="figure">
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<img src="movie_analysis/genre_distribution.png" alt="电影类型分布">
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<p class="caption">Movie Genre Distribution</p>
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</div>
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<div class="figure">
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<img src="movie_analysis/year_distribution.png" alt="电影发行年份分布">
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<p class="caption">Movie Release Year Distribution</p>
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</div>
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<div class="figure">
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<img src="movie_analysis/most_rated_movies.png" alt="评分数量最多的电影">
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<p class="caption">Top 20 Most Rated Movies</p>
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</div>
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<h2>Rating Distribution Analysis</h2>
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<div class="figure">
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<img src="rating_analysis/rating_distribution.png" alt="评分分布">
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<p class="caption">Rating Distribution</p>
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</div>
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<div class="figure">
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<img src="rating_analysis/genre_avg_ratings.png" alt="各类型电影的平均评分">
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<p class="caption">Average Rating by Movie Genre</p>
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</div>
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<div class="figure">
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<img src="rating_analysis/top_rated_movies.png" alt="评分最高的电影">
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<p class="caption">Top 20 Highest Rated Movies (min. 100 ratings)</p>
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</div>
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<h2>User Characteristics and Movie Preferences</h2>
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<div class="figure">
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<img src="preference_analysis/gender_genre_heatmap.png" alt="不同性别的电影类型偏好">
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<p class="caption">Movie Genre Preferences by Gender</p>
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</div>
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<div class="figure">
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<img src="preference_analysis/age_genre_heatmap.png" alt="不同年龄段的电影类型偏好">
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<p class="caption">Movie Genre Preferences by Age Group</p>
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</div>
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<div class="figure">
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<img src="preference_analysis/age_year_heatmap.png" alt="不同年龄段对不同年代电影的偏好">
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<p class="caption">Preferences for Movies by Decade Across Age Groups</p>
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</div>
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<div class="figure">
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<img src="preference_analysis/gender_avg_rating.png" alt="性别与平均评分的关系">
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<p class="caption">Relationship Between Gender and Average Rating</p>
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</div>
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<h2>Conclusions and Insights</h2>
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<p>Through in-depth analysis of the MovieLens dataset, we found significant correlations between user characteristics (gender, age, occupation) and movie preferences. Key findings include:</p>
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<ul>
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<li>Significant differences in movie genre preferences between genders</li>
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<li>Age influences how users rate movies from different decades</li>
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<li>Occupational background correlates with genre preferences</li>
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</ul>
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<p>These findings provide valuable reference for designing movie recommendation systems and developing movie marketing strategies.</p>
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</div>
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</body>
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</html>
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analysis_results/analysis_summary.json
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{
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"Data Overview": {
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"Number of Users": 6040,
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"Number of Movies": 3883,
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"Original Ratings Count": 1000209,
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"Filled Ratings Count": 22384240
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},
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"User Analysis": {
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"Gender Distribution": {
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"M": 4331,
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"F": 1709
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},
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"Age Distribution": {
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"25-34": 2096,
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"35-44": 1193,
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"18-24": 1103,
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"45-49": 550,
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"50-55": 496,
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"56+": 380,
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"Under 18": 222
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}
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},
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"Rating Analysis": {
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"Average Rating": 3.58,
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"Rating Distribution": {
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"1": 56174,
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"2": 107557,
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"3": 261197,
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"4": 348971,
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"5": 226310
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}
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}
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}
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analysis_results/movie_analysis/genre_distribution.png
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analysis_results/movie_analysis/most_rated_movies.png
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